CN107146035A - The computational methods of coefficient of lot size in the production of knitted dress bulk production - Google Patents
The computational methods of coefficient of lot size in the production of knitted dress bulk production Download PDFInfo
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Abstract
The invention discloses the computational methods of coefficient of lot size in a kind of production of knitted dress bulk production, step is as follows：S1, collects enterprise's historical production data；S2, is fitted learning curve, calculates the initial workpiece man-hour a of each product orderi, learning coefficient biWith employee's learning rate c；S3, calculates the handwork ratio of each product order；S4, calculates the product difficulty of each product order；S5, determines the initial workpiece man-hour a and employee's learning rate c, handwork ratio, the relational expression of product difficulty of product order；S6, calculates the standard-run quantity of product order；S7, calculates the coefficient of lot size of product order；S8, when correcting, improving standard chief engineer.The present invention is carried out quantitative analysis to the structure and technique of product with reference to enterprise's GSD systems, is determined the quantitative relationship of coefficient of lot size and product using the line creation data of enterprise one.The computational methods are combined with the management system of enterprise, the standard work force system of perfect enterprise, provide rational basis for enterprise cost accounting, staff salary balance, improve the managerial ability of enterprise.
Description
Technical field
The invention belongs to garment production management field, the meter of coefficient of lot size in more particularly to a kind of knitted dress bulk production production
Calculation method.
Background technology
Standard work force is one of important basic management data of clothes production enterprise, is that enterprise arranges production, organizes flowing water
Line, account cost, estimate the important evidences such as profit, the whether accurate production that will directly affect enterprise of its data, manage and manage
Reason.Because standard work force is a reference value, a reference point, when enterprise with standard work force carry out plan arrangement, process layout, into
During this accounting, it is necessary to adjusted and corrected according to actual conditions, it is allowed to compared with can really reflect actual conditions.
Under the background of economic globalization, garment production pattern changes to multi items, small lot.Because product quantity is few,
Turn money fast so that garment production state is over production when not yet reaching the standard work force quota of enterprise, causes enterprise connecing
Lack scientific basis in terms of single quotation, measurement production capacity.Coefficient of lot size is just to compensate for actual batch and standard-run quantity
Between gap, and the time increase determined or discount and the coefficient set up, it is according to order batch size according to learning rate
The amendment done to standard work force quota, the revised hour norm more conforms to practical condition, makes garment production scene
Management more becomes more meticulous.
The research of coefficient of lot size derives from machine industry earliest.Initial machinery manufacturing industry list amount is few, and single products add
Long between man-hour, enterprise calculates different batches using the coefficient of lot size method of segmentation stagewise (the different coefficient of i.e. different batch correspondences)
Standard process time under amount；Hereafter correlative study person calculates coefficient of lot size by learning curve.Yang Yixiong is taught in this base
Proposed on plinth according to skilled rate, obtain coefficient of lot size value in batches than looking into coefficient of lot size table.
It is as shown in the table using the coefficient of lot size method of segmentation stagewise more than enterprise in actual production：
Enterprise's coefficient of lot size table
In actual applications, the product batch of actual production directly is compareed into coefficient of lot size table directly to use, i.e. product batch
Measure standard work force=product batch × coefficient of lot size × single-piece standard work force.This method is although easy to use, but style is different,
Processing difficulty or ease are also different, and coefficient of lot size is also different.Enterprise uses a kind of coefficient of lot size table, for all products of enterprise, deposits
In certain irrationality.In addition, the amendment of coefficient of lot size is influenceed by being segmented, deficient in stability；Batch on waypoint
There is also certain irrationality for amount quota.
In addition, based on a small amount of sample data progress learning curve simulation is artificially collected more than existing research, according to sample number
The standard-run quantity of product is determined according to subjective, then carries out the determination of product coefficient of lot size.There is certain subjective judgement in this method
Property and hysteresis quality, it is impossible to be applied to garment enterprise multi items, intelligent production well.
The content of the invention
The present invention is to solve existing coefficient of lot size calculates the technical problems such as cumbersome, subjectivity is strong, so as to provide one kind
The coefficient of lot size of order product can be easily and efficiently obtained, scientific and rational foundation is provided for the amendment in company standard man-hour,
And then enterprise is arranged production, produce quotation, account cost, estimate profit etc. provide foundation knitted dress bulk production production in batch
The computational methods of coefficient of discharge.
In order to solve the above technical problems, the technical solution adopted in the present invention is as follows：In a kind of knitted dress bulk production production
The computational methods of coefficient of lot size, step is as follows：S1, collects enterprise's history according to the RFID system of enterprise or hangar system and produces number
According to；
The historical production data need to include product order number, production time, the daily output, working time day etc., and to receiving
The enterprise's production line historical production data collected is arranged, and the creation data of each product is pressed into the production time from morning to night
It is ranked up.
S2, learning curve fitting, calculates the initial workpiece man-hour a of each product orderi, learning coefficient biWith employee's learning rate c；
S2.1, according to historical production data, cumulative production, accumulative man-hour, the accumulative single-piece for calculating each product order are put down
Equal man-hour.Specifically, using the yield at the yield of last procedure of group or group inspection as the daily output on the same day, all lifes are asked
The daily output average of each group of the product order is produced as the daily average operation time conduct of the daily output of the product, group
Process time day of the product, calculate the accumulative daily output, accumulative man-hour, the accumulative single-piece average man-hours, calculation formula of product
It is as follows：
The accumulative daily output=∑ product daily output；
Accumulative man-hour=∑ product day process time；
S2.2, sets up the learning curve of product order, is specially：
Y=aX-b(1)；
Wherein, Y represents to produce the accumulative average man-hours of X part products；X is cumulative production；A is initial workpiece man-hour；B is study
Coefficient, 0<b<1, andC is employee's learning rate.
S2.3, the calculating data in step S2.1, is fitted to the learning curve in step S2.2, obtains each
The initial workpiece man-hour a of product orderi, learning coefficient biWith employee's learning rate ci, wherein, i represents product order number, i ∈ [1, n],
n∈N+。
S3, calculates the handwork ratio of each product order.
The handwork ratio of each product order has two kinds of calculations, and a kind of acted according to the GSD of each order product
Analysis, draws the handwork ratio of each product order, calculation formula is：
Another is to carry out handwork ratio calculating according to the process type of each product order, and calculation formula is
Because the most processes of product need man-machine cooperation, influenceed larger by employee skill level in actual production,
When handling the process of man-machine cooperation, the process of man-machine cooperation is considered as the mechanical work time, it is to avoid done by employee skill level
Disturb.
S4, calculates each product difficulty.
Concretely comprise the following steps：S4.1, the pure total elapsed time of each product order is determined according to enterprise's GSD systems；
S4.2, calculates the standard total elapsed time of each product order；
Calculation formula is：Standard total elapsed time=pure total elapsed time × (the floating remaining rates of 1+) (4)；
S4.3, according to the custom of enterprise's dividing step, obtains the process that link is sewed in each product order actual production
Operation quantity included in list；
S4.4, the product difficulty of each product order is calculated according to step 4.2 and step 4.3；
S5, determines the initial workpiece man-hour a and employee's learning rate c, handwork ratio, the relation of product difficulty of product order
Formula.
Concretely comprise the following steps：S5.1, sets up the initial workpiece man-hour a and employee's learning rate c of product order, handwork ratio, production
The relational model of product difficulty, be specially：
Y=ω+α × x1+β×x2+γ×x3(6)；
Wherein, x1Represent handwork ratio, x2Represent product difficulty, x3Represent that product familiarity c, y represent initial workpiece man-hour
a；ω is constant, and α, β, γ are respectively coefficient；
S5.2, according to the handwork ratio, product difficulty, product familiarity c of each product order calculated in step 2-4
Substitute into relational model and be fitted respectively with initial workpiece man-hour a, obtain ω, α, β, γ numerical value, and then obtain coefficient determination
Relational model.
S6, calculates the standard-run quantity of product order；
S6.1, to the learning curve derivation in step S2, obtains single order derived function y '：
Y '=- abx-b-1(7)；
S6.2, to single order derived function y ' solutions, obtains the standard-run quantity of product order；
Make y '=- abx-b-1=-0.08 (8)；
Calculate and obtain the standard-run quantity of product order and be
S7, calculates the coefficient of lot size of product order；
Calculation formula is：
S8, when correcting, improving standard chief engineer
According to the coefficient of lot size of the product order obtained in step S7, it is modified during to the standard chief engineer of product order；
Correction formula is：
During the standard chief engineer of amendment=standard chief engineer when × coefficient of lot size (10).
A line creation data of the invention based on collections such as RFID systems, the sequence information of combination product, according to enterprise GSD
When system draws the standard chief engineer of product, operation quantity and handwork ratio；Product is obtained by being fitted to data
Initial workpiece man-hour a, learning coefficient b and learning rate c, then carry out regression analysis, draw product difficulty, handwork ratio and product
Familiarity, learning rate intuitively reflects familiarity of the employee to a certain product, therefore characterizes product familiarity with learning rate c,
With product initial workpiece man-hour a relational expression；Determine learning curve derivative y '=- abx-b-1Cumulative production x when=- 0.08 is standard batch
Amount, product standard batch is determined by solving x；The coefficient of lot size of product is determined according to the calculation formula of coefficient of lot size afterwards.This hair
It is bright easily and efficiently to obtain the coefficient of lot size of order product, for company standard man-hour amendment provide it is scientific and rational according to
According to, and then enterprise is arranged production, quotation, account cost is produced, the offer foundation such as profit is provided.Batch designed by the present invention
Coefficient calculation method, standard total elapsed time, operation quantity, handwork ratio and employee of decomposition in known product
Coefficient of lot size of the product under certain order volume can be directly obtained in the case of habit rate, and then to enterprise's given standard work force
It is modified, the standard work force system of perfect enterprise, improves the administrative decision ability of enterprise.
Brief description of the drawings
Fig. 1 is learning curve figure of the present invention.
Fig. 2 is present system flow chart.
Embodiment
As shown in Figure 1-2, a kind of computational methods of coefficient of lot size during knitted dress bulk production is produced, step is as follows：S1, according to
The RFID system or hangar system of enterprise collect enterprise's historical production data；
The historical production data need to include product order number, production time, the daily output, working time day etc., and to receiving
The enterprise's production line historical production data collected is arranged, and the creation data of each product is pressed into the production time from morning to night
It is ranked up.
S2, learning curve fitting, calculates the initial workpiece man-hour a of each product orderi, learning coefficient biWith employee's learning rate c；
S2.1, according to historical production data, cumulative production, accumulative man-hour, the accumulative single-piece for calculating each product order are put down
Equal man-hour.Specifically, using the yield at the yield of last procedure of group or group inspection as the daily output on the same day, all lifes are asked
The daily output average of each group of the product order is produced as the daily average operation time conduct of the daily output of the product, group
Process time day of the product, calculate the accumulative daily output, accumulative man-hour, the accumulative single-piece average man-hours, calculation formula of product
It is as follows：
The accumulative daily output=∑ product daily output；
Accumulative man-hour=∑ product day process time；
S2.2, sets up the learning curve of product order, is specially：
Y=aX-b(1)；
Wherein, Y represents to produce the accumulative average man-hours of X part products；X is cumulative production；A is initial workpiece man-hour；B is study
Coefficient, 0<b<1, andC is employee's learning rate.
With the increase of cumulative production, the raising of employee's qualification, single product man-hour is on a declining curve, thus shape
The function curve successively decreased into a man-hour, referred to as learning curve.As shown in Figure 1.
S2.3, the calculating data in step S2.1, is fitted to the learning curve in step S2.2, obtains each
The initial workpiece man-hour a of product orderi, learning coefficient biWith employee's learning rate ci, wherein, i represents product order number, i ∈ [1, n],
n∈N+。
S3, calculates the handwork ratio of each product order.
The handwork ratio of each product order has two kinds of calculations, and a kind of acted according to the GSD of each order product
Analysis, draws the handwork ratio of each product order, calculation formula is：
Another is to carry out handwork ratio calculating according to the process type of each product order, and calculation formula is
Because the most processes of product need man-machine cooperation, influenceed larger by employee skill level in actual production,
When handling the process of man-machine cooperation, the process of man-machine cooperation is considered as the mechanical work time, it is to avoid done by employee skill level
Disturb.
S4, calculates each product difficulty.
Concretely comprise the following steps：S4.1, the pure total elapsed time of each product order is determined according to enterprise's GSD systems；
S4.2, calculates the standard total elapsed time of each product order；
Calculation formula is：Standard total elapsed time=pure total elapsed time × (the floating remaining rates of 1+) (4)；
Floating remaining rate determines that the floating remaining rate of general enterprises is more than 25% according to the managerial skills of each enterprise.
S4.3, according to the custom of enterprise's dividing step, obtains the process that link is sewed in each product order actual production
Operation quantity included in list；
S4.4, the product difficulty of each product order is calculated according to step 4.2 and step 4.3；
S5, determines the initial workpiece man-hour a and employee's learning rate c, handwork ratio, the relation of product difficulty of product order
Formula.
Concretely comprise the following steps：S5.1, sets up the initial workpiece man-hour a and employee's learning rate c of product order, handwork ratio, production
The relational model of product difficulty, be specially：
Y=ω+α × x1+β×x2+γ×x3(6)；
Wherein, x1Represent handwork ratio, x2Represent product difficulty, x3Represent that product familiarity c, y represent initial workpiece man-hour
a；ω is constant, and α, β, γ are respectively coefficient；
Before model is set up, made by Pearson came (Pearson) correlation method to initial workpiece man-hour a and employee's learning rate c, by hand
Industry ratio, product difficulty have carried out correlation analysis, and analysis is understood, initial workpiece man-hour a and employee's learning rate c, handwork ratio,
There is weaker correlation between product difficulty.
S5.2, according to the handwork ratio, product difficulty, product familiarity c of each product order calculated in step 2-4
Substitute into relational model and be fitted respectively with initial workpiece man-hour a, obtain ω, α, β, γ numerical value, and then obtain coefficient determination
Relational model.
S6, calculates the standard-run quantity of product order；
The whole process of garment production can be divided into 2 stages according to learning curve：Unit product man-hour reduces faster
The stabilization sub stage that study stage and man-hour tend towards stability.As shown in Figure 1.
Slope illustrates the variation tendency of curve.The absolute value of slope is smaller, represents learning curve more steady.Therefore this hair
Clearly determine slope in learning curve level off to 0 point as standard-run quantity reference value.That is the derived function of learning curve equation becomes
In 0 point.In order to try to achieve optimal solution,
S6.1, to the learning curve derivation in step S2, obtains single order derived function y '：
Y '=- abx-b-1(7)；
S.2, to single order derived function y ' solutions, the standard-run quantity of product order is obtained；
According to power function y=xaProperty, work as a<When 0, image is subtraction function in (0 ,+∞), there is two in first quartile
Asymptote, independent variable levels off to 0, and functional value levels off to+∞；Independent variable convergence+∞, functional value levels off to 0.Therefore formula 7 can only
0 is substantially equal to, and 0 can not be equal to.With reference to the application value of coefficient of lot size, it is believed that
When learning curve reach steadily, its corresponding x value be standard-run quantity.Even,
Y '=- abx-b-1=-0.08 (8)；
Calculate and obtain the standard-run quantity of product order and be
WhereinThen the expression formula for substituting into initial workpiece man-hour a is that can obtain the corresponding standard-run quantity of product.
S7, calculates the coefficient of lot size of product order；
Calculation formula is：
S8, when correcting, improving standard chief engineer
According to the coefficient of lot size of the product order obtained in step S7, it is modified during to the standard chief engineer of product order；
Correction formula is：
During the standard chief engineer of amendment=standard chief engineer when × coefficient of lot size (10).
The present invention is further described with a specific example below.
1) sample data
1. by taking the knitted dress enterprise of Suzhou as an example, the historical production data of enterprise's different product is collected, is carried out at data
Reason, calculates the cumulative production and accumulative average man-hours of product, using cumulative production as x-axis, and it is that y-axis carries out curve to add up average man-hours
Fitting, obtains the learning curve of product, you can obtain product initial workpiece man-hour a, learning coefficient b, learning rate c；
2. with reference to the GSD systems or the process labor cost list of product of enterprise, product pure process time, operation quantity are determined
With handwork ratio；
3. product difficulty is calculated：
When 4. calculating product standard chief engineer：During standard chief engineer=purely chief engineer when × (1+ floating remaining rate)；According to the enterprise
Managerial skills, 20% is taken by floating remaining rate；
5. during pure chief engineer that product is corresponding, during standard chief engineer, operation quantity, handwork ratio, product difficulty, learn
Practise coefficient bi, initial workpiece man-hour ai, product familiarity c collected, as shown in table 1.
The data sample of table 1 collects
2) coefficient of lot size model is set up
1. correlation analysis
Correlation analysis is carried out to initial workpiece man-hour a, product difficulty, manual ratio, product familiarity, as shown in table 2.From point
Analyse in result as can be seen that initial workpiece man-hour a and product difficulty, manual ratio, product familiarity have weaker correlation.
The initial workpiece man-hour a of table 2 and product difficulty, manual ratio, the correlation analysis of product familiarity
* correlations notable (double tails) on 0.01 layer.
2. initial workpiece man-hour a models are set up
After phase relation analysis, regression analysis, structure are carried out to initial workpiece man-hour a, product difficulty, manual ratio, product familiarity
Linear model is built, coefficient of determination R is obtained2About 0.968, coefficient of determination is about 0.963 after adjustment, illustrates the modelling effect set up
Preferably.As shown in table 3.
The model of table 3 collects
Table 4 show the analysis of variance table of regression model.It can be seen that F statistic=182.68 in the results of analysis of variance,
Probability P value=0.0002 is less than significance 0.05, so the model has statistical significance.
The analysis of variance table of table 4
Table 5 gives the regression coefficient table of model.VIF values are less than 10, illustrates between three independents variable in the absence of multiple common
Linearly.
The regression coefficient table of table 5
Therefore the regression equation constructed by model is
Initial workpiece man-hour a=46591.918-1703.427 × craft ratio+63.388 × product difficulty -50207.515=
Product proficiency；
Use x1Represent handwork ratio, x2Represent product difficulty, x3Product familiarity is represented, y represents initial workpiece man-hour a, then
Y=46591.918-1703.427x1+63.388x2-50207.515x3；
3. product standard batch is calculated
Calculate product standard-run quantity when, exactly differentiate for -0.08 x values.
Y '=- abx-b-1=-0.08
4. coefficient of lot size model
The calculation formula of coefficient of lot size is
3) coefficient of lot size model application
It is 26 that enterprise's money product, which carries out its operation quantity after process decomposition, and it is 18.42% to calculate its manual ratio, pure
632.5s during pure chief engineer, employee is 90% to the proficiency of product, and order volume is 2000.
Determining the method for product learning rate has historical summary method, the experience estimation technique, direct measuring method, synthetic method.
1. historical summary method
According to the historical production data of enterprise, its corresponding learning efficiency is studied.When carrying out learning rate prediction to product,
According to current production and the style similarity of product, technique similitude etc. before, direct usage history learning rate or to study
Rate is suitably increased or decreased.This method needs enterprise to have certain data accumulation, and production management system is perfect, ability and history
Order is contrasted.But there is certain error and subjectivity in this method.
2. empirical estimation method
When enterprise is not or when lacking the learning rate of similar products, it can be provided according to the history for the enterprise for producing same product
Material or the experience according to administrative staff, are set with reference to the practical condition of enterprise.Generally, learning rate can root
The learning rate of product is determined according to the method shown in table 6.
The learning rate empirical estimation method of table 6
3. direct measuring method
Research object is chosen, process time test is carried out on streamline by IE personnel, at least 30 samples are generally required
(suitably increasing sample size according to the condition of production of employee), calculates sample value afterwards, and described point fits its corresponding
Curve is practised, so as to draw the learning coefficient of employee.Further according toObtain learning rate c.This method person of depending primarily on
The accuracy of the test sample of work, is applicable to the trendy test reached the standard grade.
4. synthetic method
During garment production, product can be divided into multiple working procedure.The learning rate of every procedure can be tested respectively, afterwards according to every
The proportion when standard work force of procedure accounts for product standard chief engineer enters as the weight of every procedure to the learning rate of every procedure
Row weighted average is the learning rate that can obtain product.This method is the most accurate, as a result relatively reliable.
Product difficulty is
Respective formula is substituted into, it is 2941 to obtain its product initial workpiece man-hour a；
Respective formula is substituted into, learning coefficient b is obtained：
Respective formula is substituted into, the standard-run quantity for obtaining product is 5514；
Respective formula is substituted into, it is 1.16 to obtain coefficient of lot size；
It is 632.5 × 1.2 × 1.16=880.44s during revised standard chief engineer.
Therefore, only it is to be understood that during the pure chief engineer of product, floating remaining rate, operation quantity, handwork ratio, product familiarity
The coefficient of lot size of the product under certain order volume can be calculated.
The present invention is quantified using the line creation data of enterprise one with reference to enterprise's GSD systems to the structure and technique of product
Analysis, determines the quantitative relationship of coefficient of lot size and product.Method, the result that this method is drawn are determined compared to other coefficient of lot size
More science, conveniently.Enterprise can according to the standard chief engineer of product when, operation quantity, handwork ratio, employee's learning rate, order
Single coefficient of lot size for directly obtaining product in batches under correspondence batch.The computational methods and the management system of enterprise can mutually be tied
Close, the standard work force system of perfect enterprise, provide rational basis for enterprise cost accounting, staff salary balance, improve enterprise
Managerial ability.
Claims (7)
1. the computational methods of coefficient of lot size in a kind of knitted dress bulk production production, it is characterised in that：Step is as follows：S1, according to enterprise
The RFID system or hangar system of industry collect enterprise's historical production data；
S2, learning curve fitting, calculates the initial workpiece man-hour a of each product orderi, learning coefficient biWith employee's learning rate c；
S3, calculates the handwork ratio of each product order；
S4, calculates the product difficulty of each product order；
The calculation formula of product difficulty is：
S5, determines the initial workpiece man-hour a and employee's learning rate c, handwork ratio, the relational expression of product difficulty of product order：
Specially：
Y=ω+α × x1+β×x2+γ×x3(6)；
Wherein, x1Represent handwork ratio, x2Represent product difficulty, x3Represent that product familiarity c, y represent initial workpiece man-hour a；ω
For constant, α, β, γ are respectively coefficient；
S6, calculates the standard-run quantity of product order；
S7, calculates the coefficient of lot size of product order；
Calculation formula is：
S8, when correcting, improving standard chief engineer；
Correction formula is：During the standard chief engineer of amendment=standard chief engineer when × coefficient of lot size (11).
2. the computational methods of coefficient of lot size in knitted dress bulk production production according to claim 1, it is characterised in that：In step
In rapid S1, the historical data includes product order number, production time, the daily output, working time day.
3. the computational methods of coefficient of lot size in knitted dress bulk production production according to claim 1, it is characterised in that：In step
In rapid S2, concretely comprise the following steps；S2.1, according to historical production data, calculate the cumulative production of each product order, accumulative man-hour,
Accumulative single-piece average man-hours；
Specifically, using the yield at the yield of last procedure of group or group inspection as the daily output on the same day, all productions are asked
The daily output average of each group of the product order is used as this daily average operation time as the daily output of the product, group
Process time day of product, the accumulative daily output, accumulative man-hour, the accumulative single-piece average man-hours of product are calculated, calculation formula is such as
Under：
The accumulative daily output=∑ product daily output；
Accumulative man-hour=∑ product day process time；
S2.2, sets up the learning curve of product order, is specially：
Y=aX-b(1)；
Wherein, Y represents to produce the accumulative average man-hours of X part products；X is cumulative production；A is initial workpiece man-hour；B is study system
Number, 0<b<1, andC is employee's learning rate；
S2.3, the calculating data in step S2.1, is fitted to the learning curve in step S2.2, obtains each product
The initial workpiece man-hour a of orderi, learning coefficient biWith employee's learning rate ci, wherein, i represents product order number, i ∈ [1, n], n ∈ N+。
4. the computational methods of coefficient of lot size in knitted dress bulk production production according to claim 1, it is characterised in that：In step
In rapid S3, the handwork ratio of each product order has two kinds of calculations, and a kind of is according to the GSD of each order product actions point
Analysis, draws the handwork ratio of each product order, calculation formula is：
Another is to carry out handwork ratio calculating according to the process type of each product order, and calculation formula is：
Because the most processes of product need man-machine cooperation, influenceed larger by employee skill level in actual production, in processing
During the process of man-machine cooperation, the process of man-machine cooperation is considered as the mechanical work time, it is to avoid disturbed by employee skill level.
5. the computational methods of coefficient of lot size in knitted dress bulk production production according to claim 1, it is characterised in that：In step
In rapid S4, concretely comprise the following steps；S4.1, the pure total elapsed time of each product order is determined according to enterprise's GSD systems；
S4.2, calculates the standard total elapsed time of each product order；Calculation formula is：
Standard total elapsed time=pure total elapsed time × (the floating remaining rates of 1+) (4)；
S4.3, according to the custom of enterprise's dividing step, is obtained in each product order actual production in the planning sheet of sewing link
Comprising operation quantity；
S4.4, the product difficulty of each product order is calculated according to step 4.2 and step 4.3；
6. the computational methods of coefficient of lot size in knitted dress bulk production production according to claim 1, it is characterised in that：In step
In rapid S5, concretely comprise the following steps；S5.1, sets up the initial workpiece man-hour a and employee's learning rate c, handwork ratio, product of product order
The relational model of difficulty, be specially：
Y=ω+α × x1+β×x2+γ×x3(6)；
Wherein, x1Represent handwork ratio, x2Represent product difficulty, x3Represent that product familiarity c, y represent initial workpiece man-hour a；ω
For constant, α, β, γ are respectively coefficient；
S5.2, according to the handwork ratio, product difficulty, product familiarity c and head of each product order calculated in step 2-4
Part man-hour a is substituted into relational model respectively to be fitted, and obtains ω, α, β, γ numerical value, and then obtain the relation of coefficient determination
Model.
7. the computational methods of coefficient of lot size in knitted dress bulk production production according to claim 1, it is characterised in that：In step
In rapid S6, concretely comprise the following steps；S6.1, to the learning curve derivation in step S2, obtains single order derived function y '：
Y '=- abx-b-1(7)；
S6.2, to single order derived function y ' solutions, obtains the standard-run quantity of product order；
Make y '=- abx-b-1=-0.08 (8)；
Calculate and obtain the standard-run quantity of product order and be
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